Triple
T8667461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ajith Kumar |
E205711
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Aalwar
Aalwar is a 2007 Tamil-language action drama film starring Ajith Kumar, known for its themes of revenge and vigilantism.
|
E751746
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Aalwar | Statement: [Ajith Kumar, notableWork, Aalwar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aalwar Context triple: [Ajith Kumar, notableWork, Aalwar]
-
A.
Bhabra
Bhabra is a town in the Alirajpur district of Madhya Pradesh, India, known as the birthplace of Indian revolutionary Chandra Shekhar Azad.
-
B.
Bhailsa
Bhailsa is the former historical name of Vidisha, an ancient city in the central Indian state of Madhya Pradesh known for its rich archaeological and cultural heritage.
-
C.
Sakesar
Sakesar is a prominent mountain peak in Pakistan’s Punjab region, known for its scenic views, cooler climate, and strategic location within the Salt Range.
-
D.
Anup Talao
Anup Talao is an ornamental, quadrilateral water tank in the royal complex of Fatehpur Sikri, known for its central platform and association with Emperor Akbar’s court.
-
E.
Kalgidhar
Kalgidhar is an honorific epithet of Guru Gobind Singh, emphasizing his revered status as a timeless, divine protector in Sikh tradition.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Aalwar Triple: [Ajith Kumar, notableWork, Aalwar]
Generated description
Aalwar is a 2007 Tamil-language action drama film starring Ajith Kumar, known for its themes of revenge and vigilantism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aalwar Target entity description: Aalwar is a 2007 Tamil-language action drama film starring Ajith Kumar, known for its themes of revenge and vigilantism.
-
A.
Bhabra
Bhabra is a town in the Alirajpur district of Madhya Pradesh, India, known as the birthplace of Indian revolutionary Chandra Shekhar Azad.
-
B.
Bhailsa
Bhailsa is the former historical name of Vidisha, an ancient city in the central Indian state of Madhya Pradesh known for its rich archaeological and cultural heritage.
-
C.
Sakesar
Sakesar is a prominent mountain peak in Pakistan’s Punjab region, known for its scenic views, cooler climate, and strategic location within the Salt Range.
-
D.
Anup Talao
Anup Talao is an ornamental, quadrilateral water tank in the royal complex of Fatehpur Sikri, known for its central platform and association with Emperor Akbar’s court.
-
E.
Kalgidhar
Kalgidhar is an honorific epithet of Guru Gobind Singh, emphasizing his revered status as a timeless, divine protector in Sikh tradition.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48a34b808190aa9aed9cdb2900e6 |
completed | March 31, 2026, 10:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef3898bf88190959b361638d032de |
completed | April 2, 2026, 10:54 p.m. |
| NEDg | Description generation | batch_69cef4cbc0788190bf95aa8058a8d895 |
completed | April 2, 2026, 10:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cef830e4e48190bf337a526cc82119 |
completed | April 2, 2026, 11:13 p.m. |
Created at: March 30, 2026, 6:31 p.m.